Evidence map›Paper›PMID 31760268›Full record

ArticleTranslational oncology2020

Molecular Pathway Analysis Indicates a Distinct Metabolic Phenotype in Women With Right-Sided Colon Cancer.

Yazhi Sun, Varvara Mironova, Ying Chen, Elliott P F Lundh, Qian Zhang, Yuping Cai, Vasilis Vasiliou, Yawei Zhang, Rolando Garcia-Milian, Sajid A Khan and 1 more

Open access · goldAbstract read
In one paragraph

Article in Translational oncology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
2.2field-weighted citation impact, top 10% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 20 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 2 institutions in 2 countries.

Yazhi SunDepartment of Environmental Health Sciences, Yale School of Public Health, Yale University, New Haven, CT USA.
Varvara MironovaDepartment of Environmental Health Sciences, Yale School of Public Health, Yale University, New Haven, CT USA; Department of Surgery, Section of Surgical Oncology, Yale University School of Medicine, New Haven, CT, USA.
Ying ChenDepartment of Environmental Health Sciences, Yale School of Public Health, Yale University, New Haven, CT USA.
Elliott P F LundhDepartment of Environmental Health Sciences, Yale School of Public Health, Yale University, New Haven, CT USA.
Qian ZhangDepartment of Environmental Health Sciences, Yale School of Public Health, Yale University, New Haven, CT USA; Department of Colorectal Surgery, The Second Affiliated Hospital of Harbin Medical University, Harbin, China.
Yuping CaiDepartment of Environmental Health Sciences, Yale School of Public Health, Yale University, New Haven, CT USA.
Vasilis VasiliouDepartment of Environmental Health Sciences, Yale School of Public Health, Yale University, New Haven, CT USA.
Yawei ZhangDepartment of Environmental Health Sciences, Yale School of Public Health, Yale University, New Haven, CT USA; Department of Surgery, Yale University School of Medicine, New Haven, CT, USA.
Rolando Garcia-MilianDepartment of Environmental Health Sciences, Yale School of Public Health, Yale University, New Haven, CT USA; Bioinformatics Support Program, Cushing/Whitney Medical Library, Yale School of Medicine, New Haven, CT, USA.
Sajid A KhanDepartment of Surgery, Section of Surgical Oncology, Yale University School of Medicine, New Haven, CT, USA.
Caroline H JohnsonDepartment of Environmental Health Sciences, Yale School of Public Health, Yale University, New Haven, CT USA. Electronic address: caroline.johnson@yale.edu.
Yale University · USWhitney Museum of American Art · US

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
Mouse Models for Alcohol Metabolism and Tissue InjuryR24AA022057 · NIAAA · YALE UNIVERSITY · PI VASILIOU, VASILIS · 2013 to 2022
$4.5M
NCATS NIH HHS UL1 TR001863NIAAA NIH HHS R24 AA022057
6 · The paper itself

Abstract

Colon cancer is the third most commonly diagnosed cancer in the United States. Recent reports have shown that the location of the primary tumor is of clinical importance. Patients with right-sided colon cancers (RCCs) (tumors arising between the cecum and proximal transverse colon) have poorer clinical outcomes than those with left-sided colon cancers (LCCs) (tumors arising between the distal transverse colon and sigmoid colon, excluding the rectum). Interestingly, women have a lower incidence of colon cancer than men, but have a higher propensity for RCC. The reason for this difference is not known; however, identification of sex-specific differences in gene expression by tumor anatomical location in the colon could provide further insight. Moreover, it could reveal important predictive markers for response to various treatments. This study provides a comprehensive bioinformatic analysis of various genes and molecular pathways that correlated with sex and anatomical location of colon cancers using four publicly available annotated data sets housed in the National Center for Biotechnology Information's Gene Expression Omnibus. We identified differentially expressed genes in tumor tissues from women with RCC, which showed attenuated energy and nutrient metabolism when compared with women with LCC. Specifically, we showed the downregulation of 5' AMP-activated protein kinase alpha subunit (AMPKα) and anti-tumor immune responses in women with RCC. This difference was not seen when comparing tumor tissues from men with RCC to men with LCC. Therefore, women with RCC may have a specific metabolic and immune phenotype which accounts for differences in prognosis and treatment response.

Identifiers

PMID31760268
PMCPMC6883319
OpenAlexW2991134771

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.